Concurrency bugs are one of the most harmful and hard-to-address issues in multithreaded software. Such bugs are hard to discover, reproduce, diagnose or fix due to their non-deterministic nature. Although more and more bug discovery solutions are proposed in recent years, it is difficult to evaluate them with existing concurrency bug datasets. The demand for building a high-quality benchmark of concurrency bugs emerges.

A growing number of bugs have been reported by vulnerability discovery solutions. Among them, some bugs are hard to diagnose or reproduce, including data race bugs caused by thread interleavings. Few solutions are able to well address this issue, due to the huge space of interleavings to explore. What’s worse, in security analysis scenarios, analysts usually have no access to the source code of target programs and have troubles in comprehending them.

Given the same input, a program may not behave the same in two runs due to some non-deterministic features, e.g., context switch and randomization. Such behaviors would cause non-deterministic program bugs which are hard to discover or diagnose. Record-and-replay is a promising technique to address such issues, however, performance and transparency are the main obstacles of existing works. In this poster, we propose a novel record-and-replay system named RIPT. RIPT utilizes Intel Processor Trace to record control flow information with very low overhead, and transparently captures non-deterministic sources such as system calls and signals with a kernel module. During replay, RIPT recovers the effect of non-deterministic events from the collected information, and makes target programs behave the same as recorded. We evaluate it with real-world program bugs and show that RIPT works well in practice.